Model comparison
DeepSeek V4 Pro (High) vs GPT-5.3 Codex
Head-to-head evidence from 15 shared benchmark results across 6 categories. Overall scores shown here use the public BenchAlign v5 ranking lane.
Public leaderboard positions: DeepSeek V4 Pro (High) #81 (Estimated); GPT-5.3 Codex #26 (Supported). Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.
Evidence parity. DeepSeek V4 Pro (High) and GPT-5.3 Codex share 15 comparable benchmark results. 2 of 8 categories are comparable. 23 results are unique to DeepSeek V4 Pro (High); 6 to GPT-5.3 Codex.
Updated July 23, 2026- Shared results
- 15
- DeepSeek V4 Pro (High) only
- 23
- GPT-5.3 Codex only
- 6
- Comparable categories
- 2 / 8
Pick GPT-5.3 Codex if you want the stronger benchmark profile. DeepSeek V4 Pro (High) only becomes the better choice if coding is the priority or you want the cheaper token bill.
Confidence note. This is a partial-evidence comparison with 15 shared benchmark results across 6 evidence categories; 2 of 8 categories currently have scoreable aggregates for both models. Treat the verdict as directional until coverage is more balanced.
Why this result
GPT-5.3 Codex is clearly ahead on the BenchAlign aggregate, 66.69 to 55.47. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
GPT-5.3 Codex's sharpest advantage is in agentic, where it averages 71.4 against 70.6. The single biggest benchmark swing on the page is Terminal-Bench 2.0, 63.3% to 77.3%. DeepSeek V4 Pro (High) does hit back in coding, so the answer changes if that is the part of the workload you care about most.
GPT-5.3 Codex is also the more expensive model on tokens at $1.75 input / $14.00 output per 1M tokens, versus $0.43 input / $0.87 output per 1M tokens for DeepSeek V4 Pro (High). That is roughly 16.1x on output cost alone. DeepSeek V4 Pro (High) gives you the larger context window at 1M, compared with 400K for GPT-5.3 Codex.
Category breakdown
Exact category averages are shown below. Not measured means BenchLM does not have enough sourced public coverage for that model and category.
| Category | DeepSeek V4 Pro (High) | Δ | GPT-5.3 Codex |
|---|---|---|---|
| Coding | DeepSeek V4 Pro (High)69.8 | Margin← 2.6 | GPT-5.3 Codex67.2 |
| Agentic | DeepSeek V4 Pro (High)70.6 | Margin→ 0.8 | GPT-5.3 Codex71.4 |
| Knowledge | DeepSeek V4 Pro (High)57.0 | MarginNo overlap | GPT-5.3 CodexNot measured |
| Math | DeepSeek V4 Pro (High)94.0 | MarginNo overlap | GPT-5.3 CodexNot measured |
Decisive benchmark drivers
The largest measured benchmark gaps in this matchup, with exact reported values.
More
- Source ↗
Terminal-Bench 2.0
AgenticA 63.3%B 77.3%Winner: GPT-5.3 CodexΔ 14Terminal-Bench 2.0: DeepSeek V4 Pro (High) scored 63.3%; GPT-5.3 Codex scored 77.3%. GPT-5.3 Codex wins this benchmark. - Source ↗
SWE-bench Verified
CodingA 79.4%B 85%Winner: GPT-5.3 CodexΔ 5.6SWE-bench Verified: DeepSeek V4 Pro (High) scored 79.4%; GPT-5.3 Codex scored 85%. GPT-5.3 Codex wins this benchmark. - Source ↗
SWE-bench Pro
CodingA 54.4%B 56.8%Winner: GPT-5.3 CodexΔ 2.4SWE-bench Pro: DeepSeek V4 Pro (High) scored 54.4%; GPT-5.3 Codex scored 56.8%. GPT-5.3 Codex wins this benchmark.
Operational comparison
Runtime and commercial metrics are compared only when both models have a complete sourced value.
| Metric | DeepSeek V4 Pro (High) | GPT-5.3 Codex | Comparison |
|---|---|---|---|
| Input / output priceUSD per 1M tokens | DeepSeek V4 Pro (High)$0.435 input / $0.87 output | GPT-5.3 Codex$1.75 input / $14 output | DeepSeek V4 Pro (High) has the lower combined listed price. |
| Generation speedtokens per second | DeepSeek V4 Pro (High)Not available | GPT-5.3 Codex79 tok/s | A complete speed comparison is not available. |
| First-answer latencyseconds to first token | DeepSeek V4 Pro (High)Not available | GPT-5.3 Codex88.26 s | A complete latency comparison is not available. |
| Context windowmaximum listed tokens | DeepSeek V4 Pro (High)1M | GPT-5.3 Codex400K | DeepSeek V4 Pro (High) lists the larger context window. |
Benchmark Deep Dive
AgenticGPT-5.3 Codex wins12 benchmarks
| Benchmark | DeepSeek V4 Pro (High) | GPT-5.3 Codex | Result |
|---|---|---|---|
| Terminal-Bench 2.0Source | 63.3% | 77.3% | GPT-5.3 Codex leads |
| BrowseCompSource | 80.4% | — | Not comparable |
| HLE w/ toolsSource | 44.7% | — | Not comparable |
| MCP AtlasSource | 74.2% | — | Not comparable |
| ToolathlonSource | 49% | — | Not comparable |
| τ²-bench resultsSource | 94.2% | 86% | DeepSeek V4 Pro (High) leads |
| GDPval-AASource | 39.9% | — | Not comparable |
| GDPval-AASource | 1299 | — | Not comparable |
| AA Agentic IndexSource | 34.4% | — | Not comparable |
| OSWorld-VerifiedSource | — | 64.7% | Not comparable |
| Gert LabsSource | — | 57.47% | Not comparable |
| JobBenchSource | — | 33.7% | Not comparable |
CodingDeepSeek V4 Pro (High) wins9 benchmarks
| Benchmark | DeepSeek V4 Pro (High) | GPT-5.3 Codex | Result |
|---|---|---|---|
| CodeforcesSource | 2919.0 | — | Not comparable |
| SWE-bench VerifiedSource | 79.4% | 85% | GPT-5.3 Codex leads |
| SWE-bench ProSource | 54.4% | 56.8% | GPT-5.3 Codex leads |
| SWE MultilingualSource | 74.1% | — | Not comparable |
| Terminal-Bench 2.0Source | 63.3% | — | Not comparable |
| AA-SciCodeSource | 46.4% | 53.2% | GPT-5.3 Codex leads |
| AA Coding IndexSource | 58.7% | — | Not comparable |
| SWE-RebenchSource | — | 58.2% | Not comparable |
| Vibe Code BenchSource | — | 61.77% | Not comparable |
Reasoning4 benchmarks
Knowledge12 benchmarks
| Benchmark | DeepSeek V4 Pro (High) | GPT-5.3 Codex | Result |
|---|---|---|---|
| MMLU-ProSource | 87.1% | — | Not comparable |
| SimpleQASource | 46.2% | — | Not comparable |
| Chinese-SimpleQASource | 77.7% | — | Not comparable |
| GPQASource | 89.1% | — | Not comparable |
| GPQA-DSource | 89.1% | — | Not comparable |
| HLESource | 34.5% | — | Not comparable |
| Artificial Analysis Intelligence IndexSource | 43.1% | 44.3% | GPT-5.3 Codex leads |
| AA-GPQA DiamondSource | 90.5% | 91.5% | GPT-5.3 Codex leads |
| AA-HLESource | 33.5% | 39.9% | GPT-5.3 Codex leads |
| AA-Omniscience IndexSource | -9.7% | 9.9% | GPT-5.3 Codex leads |
| AA-Omniscience AccuracySource | 41.8% | 51.8% | GPT-5.3 Codex leads |
| AA-Omniscience Hallucination RateSource | 88.6% | 86.9% | GPT-5.3 Codex leads |
Math4 benchmarks
Multimodal2 benchmarks
Inst. Following1 benchmarks
| Benchmark | DeepSeek V4 Pro (High) | GPT-5.3 Codex | Result |
|---|---|---|---|
| AA-IFBenchSource | 71.3% | 75.4% | GPT-5.3 Codex leads |
Frequently Asked Questions (3)
Which is better, DeepSeek V4 Pro (High) or GPT-5.3 Codex?
GPT-5.3 Codex is ahead on BenchLM's BenchAlign leaderboard, 66.69 to 55.47. The biggest single separator in this matchup is Terminal-Bench 2.0, where the scores are 63.3% and 77.3%.
Which is better for coding, DeepSeek V4 Pro (High) or GPT-5.3 Codex?
DeepSeek V4 Pro (High) has the edge for coding in this comparison, averaging 69.8 versus 67.2. Inside this category, AA-SciCode is the benchmark that creates the most daylight between them.
Which is better for agentic tasks, DeepSeek V4 Pro (High) or GPT-5.3 Codex?
GPT-5.3 Codex has the edge for agentic tasks in this comparison, averaging 71.4 versus 70.6. Inside this category, Terminal-Bench 2.0 is the benchmark that creates the most daylight between them.
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